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Remote estimation of target height from unmanned aerial vehicle (UAV) images
- Source :
- Remote sensing, vol. 12, no. 21 ( 3602), pp. 1-24, 2020., Remote Sensing, Vol 12, Iss 3602, p 3602 (2020), Remote Sensing; Volume 12; Issue 21; Pages: 3602
- Publication Year :
- 2021
- Publisher :
- MDPI, 2021.
-
Abstract
- Tonini, A., Redweik, P., Painho, M., & Castelli, M. (2020). Remote estimation of target height from unmanned aerial vehicle (Uav) images. Remote Sensing, 12(21), 1-24. [3602]. https://doi.org/10.3390/rs12213602 This paper focuses on how the height of a target can be swiftly estimated using images acquired by a digital camera installed into moving platforms, such as unmanned aerial vehicles (UAVs). A pinhole camera model after distortion compensation was considered for this purpose since it does not need extensive processing nor vanishing lines. The pinhole model has been extensively employed for similar purposes in past studies but mainly focusing on fixed camera installations. This study analyzes how to tailor the pinhole model for gimballed cameras mounted into UAVs, considering camera parameters and flight parameters. Moreover, it indicates a solution that foresees correcting only a few needed pixels to limit the processing overload. Finally, an extensive analysis was conducted to define the uncertainty associated with the height estimation. The results of this analysis highlighted interesting relationships between UAV‐to‐target relative distance, camera pose, and height uncertainty that allow practical exploitations of the proposed approach. The model was tested with real data in both controlled and uncontrolled environments, the results confirmed the suitability of the proposed method and outcomes of the uncertainty analysis. Finally, this research can open consumer UAVs to innovative applications for urban surveillance. publishersversion published
- Subjects :
- Image distortion compensation
business.product_category
Computer science
UAV
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Earth and Planetary Sciences(all)
ComputerApplications_COMPUTERSINOTHERSYSTEMS
02 engineering and technology
010501 environmental sciences
01 natural sciences
Remote surveillance
Compensation (engineering)
Limit (music)
0202 electrical engineering, electronic engineering, information engineering
Computer vision
lcsh:Science
uncertainty analysis
0105 earth and related environmental sciences
Digital camera
Pinhole model
Pixel
image distortion compensation
business.industry
Distortion (optics)
pinhole model
target height
Target height
udc:659.2:004
Uncertainty analysis
General Earth and Planetary Sciences
Pinhole camera model
lcsh:Q
020201 artificial intelligence & image processing
Pinhole (optics)
SDG 9 - Industry, Innovation, and Infrastructure
remote surveillance
Artificial intelligence
business
Subjects
Details
- Language :
- English
- ISSN :
- 20724292
- Database :
- OpenAIRE
- Journal :
- Remote sensing, vol. 12, no. 21 ( 3602), pp. 1-24, 2020., Remote Sensing, Vol 12, Iss 3602, p 3602 (2020), Remote Sensing; Volume 12; Issue 21; Pages: 3602
- Accession number :
- edsair.doi.dedup.....ff130ad075ea42fa7711fb857f69743c